Demographics Key to Transit versus Ride-Hail Choice

Ride-hailing apps for services such as Uber and Lyft have brought transportation into a whole new and very temporal world. Together these two apps alone account for millions of rides annually, while globally the industry accounts for billions.

Ride-hailing vs. Public Transit: Preferences

This trend raises some questions: Are these new trips that customers wouldn't have taken before? Or, is ride-hailing replacing trips on public transit? If ride-hailing trips are replacing trips on public transit, then why and what factors are causing this shift?

In "Trade Uber for the Bus?" in the Journal of the American Planning Association (Vol. 86, No. 2), author Xiaoxia Dong investigates why individuals use ride-hailing versus public transit and the implications for their preferences for planning. To do this Dong surveyed the Philadelphia region and analyzed respondent preferences for the two options.

Reasons why respondents chose ride-hail over transit for their last ride-hail trips (respondents could choose up to three options). From "Trade Uber for the Bus?" in Journal of the American Planning Association (Vol. 86, No. 2).

Dong's models suggest that demographics are key factors in predicting a respondent's choice of ride-hail versus transit, particularly indicating that respondents under the age of 30 are less willing to choose ride-hail over transit. Conversely, the willingness to choose ride-hail gradually increases with age for respondents over the age of 30. This shows that age affects the balance of factors affecting riders' decisions.

In addition to age, gender was a significant component. Although actual ride-hail usage rates were comparable between genders in the survey, female respondents were 1.2 times more likely to opt for ride-hail in the choice experiment. Dong notes that this indicates more than simple economic and time considerations, and concerns such as safety could be informing their decisions.

The models also show that higher-income respondents are more willing to choose ride-hail over transit.

Cost, Time, Comfort Shape Transport Choices

Dong finds that "for the average respondents, each additional $1,000 in annual household income corresponds with a 0.6 percent increase in the odds of choosing ride-hail over transit." This pairs with another of his findings that each additional dollar cost decreases respondent willingness to choose either form of transport by 7.8 percent to 8.7 percent.

However, the models also suggest that though money matters, fare reductions themselves may not be meaningful. Dong observes that "reducing the base transit fare from the current $2.50 to $1.50, a 40 percent reduction, leads to a mere 1.2 percent higher probability of choosing transit over ride-hail." He contrasts that with 15 percent reductions in wait time, walk time, and in-vehicle time, which on average increased willingness to use transit by 5 percent.

This demonstrates that rather than the actual cash costs of transport determining choice, perceived costs of time, convenience, and comfort may make more of an impact.

Furthermore, the fact that a reduction in time spent on transit is more important than cost hints at a stark truth. The drop in public transit ridership when ride-hailing emerged shows that public transit fails to adequately serve the public, in the case of Philadelphia and likely much of the U.S. Perhaps the ridership before was simply a captive market unable to make other choices.

One consideration is that this may point to an issue of critical mass. If total time spent is the operative factor, then public transit may have to reach a certain size and breadth for it to be successful and competitive.

Arguably, this is where American cities diverge most from Europe and East Asia. In the U.S., access to public transit is a privilege. In the other two areas, it's often a norm.

Dong's findings are critical to designing new transit and improving old. They show who a person is, what their habits are, and what they feel comfortable with all serve to affect their transit choices. Recognizing this, it is then in the hands of planners to design transit services to meet and balance those diverse needs.

It cannot be assumed that transit improvements will improve transit quality equally for all riders. Dong's preference models show that different groups are making different decisions based on different needs. Pointed improvements for particular populations may be a more effective and equitable means for transit improvement.

Top image: Getty Images photo.